The Power of Big Data in Logistics
Big data is revolutionising many industries, and logistics is a perfect candidate due to its dynamic and complex nature. There are so many moving parts and opportunities for driving efficiencies such as optimised routing, track and trace, and streamlining factory operations.
Big Data Sources
It is likely to already be a substantial amount of data within the organisation coming from the following sources:
- Traffic and weather data from sensors, and external forecasters
- Business data such as financial forecasts and social media responses
- Website browsing data
- Vehicle driving patterns and locations
- Route lists
For big data to be positive as opposed to a burden, there must be high-quality data sources, efficient data gathering, and exceptional data management. There are a number of business intelligence tools that are answering this requirement and providing self-service platforms. This is a huge step forward from having to call around numerous partners and rifle through stacks of paperwork to get the information needed.
The Key Benefits
If vehicles and shipments are fitted with sensors, they can feedback their location in real-time which will provide a huge amount of transparency. In its raw form, this is a lot of data being fed back in – however, with some rules set up for alerts – notifications can be sent when a vehicle or shipment is not running to schedule. This early alert can be used to potentially re-route the vehicle or shipment. Another interesting advantage is during the contract bidding phase, prospective new clients can access sensor data for the logistics companies to validate the performance data being shared.
Logistics companies have a huge focus on optimisation because it helps them to avoid late shipments and to save money. There are a number of resources being managed and planning routes, vehicles, drivers, and shipments is a complex task – particularly if it is done manually. Data can be used to handle the challenges of optimisation.
More complex information can be held about customers which helps them to be served better and relationships can be improved across the board. Furthermore, if there is an issue with a shipment, customers can be informed promptly which enhances customer satisfaction.
It is not possible to predict demand with 100% accuracy but using historical purchasing data, current client information, and other external data sources, it should be possible with big data to make it more of a reality than ever before.
There is nothing new about the importance of data to business operations. However, what big data is really about is the ability to use technology to manage huge data sets from multiple sources/feeds to allow businesses to make better and more informed decisions. Our prediction is that big data is and will continue to transform the logistics industry in positive ways.